OrynAI isn't one generalist prompt trying to do everything. It's five task-specific agents — Diagnose, Advise, Remediate, Validate, and Sequence — each grounded in your live instance and ServiceNow's official documentation, working together the way a Certified Technical Architect would: find the problem, explain it, fix it, and confirm the fix didn't break anything else.
OrynAI is the AI system behind OrynIQ's platform-health scans, chat, and remediation. Most AI tools bolted onto ServiceNow are a single prompt with a long list of tools attached — accurate at finding things, inconsistent at explaining why they matter, and silent on whether a fix actually worked. OrynAI is built as five separate agents instead, each with a narrow job and only the tools that job needs.
A finding you can't understand is hard to justify fixing. A fix you can't confirm is safe will eventually break something. OrynAI's five agents exist to close both gaps — not just surface a list of problems, but quantify them, explain them, fix them, and prove the fix held.
Every phase is grounded in your live instance, your scan data, and ServiceNow's official documentation — never a guess dressed up as an answer.
A finding without scale attached is easy to ignore. Diagnose doesn't just flag an issue — it quantifies how many records, users, or CIs it touches, and states plainly whether your platform's trajectory is improving, stable, or degrading.
Runs the compound analyzers relevant to what it's looking at, cross-referencing scan findings against real-time instance state — not a cached snapshot.
Every finding it surfaces carries an affected count, and where relevant, what percentage of your instance that represents — not just a severity label.
Improving, stable, or degrading — with the specific findings driving that call, not a vague summary.
A finding that can't be explained is hard to justify spending time on. Advise is where you ask "why does this matter" and get an answer grounded in your instance and ServiceNow's own documentation — not a training-data guess.
Role names, plugin behavior, ACL configuration, and encoded-query syntax are retrieved from ServiceNow's official documentation or read live from your instance — never stated from memory, which is where most ServiceNow AI tools get plausible-sounding details wrong.
"Per the Xanadu documentation..." or "Your instance shows..." — you know what's verified versus what's a standard-convention inference, every time.
Advise answers ServiceNow platform-health questions — yours, your industry's, your peers' — and declines what isn't, rather than improvising outside its domain to seem helpful.
Every remediation proposal states what will change, how much it affects, and why it's the right fix — before you ever see an approve button. Nothing writes to your instance without your explicit sign-off.
Every proposal is checked against a table/field allowlist your admin manages — script bodies, ACLs, schema tables, and security-critical user fields are never writable, by design, not by convention.
A proposal isn't just "change field X to Y" — it carries the same quantified magnitude Diagnose surfaces, plus the grounded reasoning for why the change is correct.
You approve, deny, or roll back — every action logged, every write immediately re-verified against your live instance.
A fix that can't be confirmed safe will eventually fail. Validate is the agent we're building to close that gap: after a fix is proposed or applied, it checks what actually depends on the thing that changed — not just whether the value we wrote is still there.
Re-reads the field after a change and confirms it matches what was written — the baseline check every remediation already gets today.
Looks up what else references the thing that changed — other scripts that call it, CIs related to it, roles that chain through it, ACLs and business rules that key off it — and re-evaluates whether those are still in a valid state.
For script and form-affecting changes, triggers an ATF regression run against a non-production instance and folds the result into its verdict.
A list of findings sorted by severity isn't a roadmap. Sequence is the agent we're building to turn a pile of validated findings into a real, dependency-aware plan — the kind of prioritization work a platform architect does by hand today.
Root-cause findings get fixed before the symptoms they cause. Fixes that would conflict with each other don't get scheduled into the same phase.
Severity and effort still matter as a tie-break — but the primary ordering comes from what actually has to happen first, not a fixed 30/60/90-day template.
Every item in the plan comes with a narrated reason for its position — never a bare ordinal you have to take on faith.
Named mechanisms, not marketing language. This is what each agent actually checks against.
Dozens of purpose-built analyzers cross-referenced against real-time instance state and ServiceNow's documentation corpus.
Official documentation, your instance, and — when neither has the answer — ServiceNow's public knowledge base, always cited.
Nothing OrynAI decides unilaterally is writable — script bodies, ACLs, schema, and security-critical fields are excluded by design.
Script call chains, CI relationships, role and group containment, field references — plus an ATF regression run where one applies. Not just "re-read the value we wrote."
Real dependency edges, not a generic severity sort — built from findings and relationships specific to your platform.
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